Abstract
In the development of a diagnostic system to monitor the condition of the frequency tuning process, fuzzy logic can be applied in recognition of unnatural statistical control chart patterns. The heuristics for reasoning is based on the principles behind statistical process control. With the experience of an expert in troubleshooting, one can derive the necessary knowledge to associate the pattern of a control chart to a set of known physical causes. Since these causes related to the unnatural statistical patterns are not independent, it is difficult to precisely associate the chart distribution patterns to the known causes. Furthermore, the causes of problems dealt with will also vary with time. Hence, by means of neural networks, it is possible to learn the association of fuzzily deduced chart patterns to plausible causes in order to achieve an optimum operating condition.
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